Measurements of climatic parameters registered over periods longer than a century constitute a unique and outstanding heritage, a quantitative memory for the territory that is a rare fortune to possess. The analysis of historical data provides important information in various fields like agriculture, industrial and tourism planning. The study of long series also takes on particular significance in relation to the analysis of possible climate change caused by man. Bra, city of Piedmont (NW Italy), has this wealth of information thanks to the naturalist Federico Craveri (1815-1890) who started in 1862 the meteorological measurements continued after by the Directors that have occurred at Craveri Museum. In this work the analysis of daily series of maximum and minimum temperature and precipitation from 1862 to 2009 starts with quality control of the series (Zhang et al., 2004). The quality control highlights some wrong values (minimum temperature higher than maximum temperature or negative precipitation) due to incorrect transcription of data. Later we have applied the homogeneity test SPLIDHOM (SPLIne Daily HOMogenization, Gruber et al., 2008) based on cubic regression that has allowed us to identify and correct the inhomogeneities in the daily series. The availability of daily homogeneous series has allowed us to begin a detailed climatic analysis aiming at identifying the climate change occurred in the territory over the past 149 years. The climatic analysis has been carried out through the study of climate indices developed by the Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI). The use of climate indices has allowed us to assess not only the variations on the average values of the meteorological variables but also the changes of the extremes values that, in most cases, have a profound impact on the society and the economy (Morberg et al., 2005 e Tank et al., 2003). For each series and each index, trends over different time scales (seasonal and annual) were calculated in order to identify the variations of the variables. The parametric Mann-Kendall test was applied to assess the statistical significance of the trends (Sneyers, 1990).
Temperature and precipitation in Bra. 149 years of meteorological observations (1862-2009)
ACQUAOTTA, FIORELLA;FRATIANNI, SIMONA
2011-01-01
Abstract
Measurements of climatic parameters registered over periods longer than a century constitute a unique and outstanding heritage, a quantitative memory for the territory that is a rare fortune to possess. The analysis of historical data provides important information in various fields like agriculture, industrial and tourism planning. The study of long series also takes on particular significance in relation to the analysis of possible climate change caused by man. Bra, city of Piedmont (NW Italy), has this wealth of information thanks to the naturalist Federico Craveri (1815-1890) who started in 1862 the meteorological measurements continued after by the Directors that have occurred at Craveri Museum. In this work the analysis of daily series of maximum and minimum temperature and precipitation from 1862 to 2009 starts with quality control of the series (Zhang et al., 2004). The quality control highlights some wrong values (minimum temperature higher than maximum temperature or negative precipitation) due to incorrect transcription of data. Later we have applied the homogeneity test SPLIDHOM (SPLIne Daily HOMogenization, Gruber et al., 2008) based on cubic regression that has allowed us to identify and correct the inhomogeneities in the daily series. The availability of daily homogeneous series has allowed us to begin a detailed climatic analysis aiming at identifying the climate change occurred in the territory over the past 149 years. The climatic analysis has been carried out through the study of climate indices developed by the Expert Team for Climate Change Detection Monitoring and Indices (ETCCDMI). The use of climate indices has allowed us to assess not only the variations on the average values of the meteorological variables but also the changes of the extremes values that, in most cases, have a profound impact on the society and the economy (Morberg et al., 2005 e Tank et al., 2003). For each series and each index, trends over different time scales (seasonal and annual) were calculated in order to identify the variations of the variables. The parametric Mann-Kendall test was applied to assess the statistical significance of the trends (Sneyers, 1990).
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